Video Data Management and Information Retrieval

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Release : 2005-01-01
Genre : Computers
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Book Rating : 467/5 ( reviews)

Video Data Management and Information Retrieval - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Video Data Management and Information Retrieval write by Sagarmay Deb. This book was released on 2005-01-01. Video Data Management and Information Retrieval available in PDF, EPUB and Kindle. This book combines the two important areas of research within computer technology and presents them in comprehensive, easy to understand manner. Ideal for graduates and under-graduates, as well as researchers working in either video data management or information retrieval, it takes an in depth look at many relevant topics within both video data management and information retrieval. In addition to dissecting those issues, it also provides a "big picture" view of each topic.

Video Data Management and Information Retrieval

Download Video Data Management and Information Retrieval PDF Online Free

Author :
Release : 2005-01-01
Genre : Computers
Kind :
Book Rating : 475/5 ( reviews)

Video Data Management and Information Retrieval - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Video Data Management and Information Retrieval write by Sagarmay Deb. This book was released on 2005-01-01. Video Data Management and Information Retrieval available in PDF, EPUB and Kindle. This book combines the two important areas of research within computer technology and presents them in comprehensive, easy to understand manner. Ideal for graduates and under-graduates, as well as researchers working in either video data management or information retrieval, it takes an in depth look at many relevant topics within both video data management and information retrieval. In addition to dissecting those issues, it also provides a "big picture" view of each topic.

Data Management for Multimedia Retrieval

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Release : 2010-05-31
Genre : Computers
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Book Rating : 585/5 ( reviews)

Data Management for Multimedia Retrieval - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Management for Multimedia Retrieval write by K. Selçuk Candan. This book was released on 2010-05-31. Data Management for Multimedia Retrieval available in PDF, EPUB and Kindle. Multimedia data require specialised management techniques because the representations of colour, time, semantic concepts, and other underlying information can be drastically different from one another. This textbook on multimedia data management techniques gives a unified perspective on retrieval efficiency and effectiveness. It provides a comprehensive treatment, from basic to advanced concepts, that will be useful to readers of different levels, from advanced undergraduate and graduate students to researchers and to professionals. After introducing models for multimedia data (images, video, audio, text, and web) and for their features, such as colour, texture, shape, and time, the book presents data structures and algorithms that help store, index, cluster, classify, and access common data representations. The authors also introduce techniques, such as relevance feedback and collaborative filtering, for bridging the 'semantic gap' and present the applications of these to emerging topics, including web and social networking.

Content-Based Video Retrieval

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Release : 2013-06-29
Genre : Computers
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Book Rating : 655/5 ( reviews)

Content-Based Video Retrieval - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Content-Based Video Retrieval write by Milan Petkovic. This book was released on 2013-06-29. Content-Based Video Retrieval available in PDF, EPUB and Kindle. The area of content-based video retrieval is a very hot area both for research and for commercial applications. In order to design effective video databases for applications such as digital libraries, video production, and a variety of Internet applications, there is a great need to develop effective techniques for content-based video retrieval. One of the main issues in this area of research is how to bridge the semantic gap between low-Ievel features extracted from a video (such as color, texture, shape, motion, and others) and semantics that describe video concept on a higher level. In this book, Dr. Milan Petkovi6 and Prof. Dr. Willem Jonker have addressed this issue by developing and describing several innovative techniques to bridge the semantic gap. The main contribution of their research, which is the core of the book, is the development of three techniques for bridging the semantic gap: (1) a technique that uses the spatio-temporal extension of the Cobra framework, (2) a technique based on hidden Markov models, and (3) a technique based on Bayesian belief networks. To evaluate performance of these techniques, the authors have conducted a number of experiments using real video data. The book also discusses domains solutions versus general solution of the problem. Petkovi6 and Jonker proposed a solution that allows a system to be applied in multiple domains with minimal adjustments. They also designed and described a prototype video database management system, which is based on techniques they proposed in the book.

Text Data Management and Analysis

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Release : 2016-06-30
Genre : Computers
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Book Rating : 186/5 ( reviews)

Text Data Management and Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Text Data Management and Analysis write by ChengXiang Zhai. This book was released on 2016-06-30. Text Data Management and Analysis available in PDF, EPUB and Kindle. Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic. This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.